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the Development of Traffic Flow Prediction Based on Deep Learning: A Literature Review 7

The Development of Traffic Flow Prediction Based on Deep Lea...

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7th international conference on computer and Communication Systems, ICCCS 2022

作者： Lei, Yongjia Cui, Zhiying Dai, Linyan Xiao, Ning Wang, Xiangjie Ma, Xiangfang Hong, Ying Jinan University International School Guangzhou China Jinan Univesity College of Cyber Security Guangzhou China Jinan University College of Information Science and Technology Guangzhou China Jinan University School of Physical Education Guangzhou China

ISBN: (数字)9781665450607

ISBN: (纸本)9781665450607

As is well acknowledged, deep learning has been fairly widely used in both academic and industrial fields in recent periods. Researchers favour its strong portability and good performance. Although deep learning has shown satisfactory performance in traffic flow prediction, its specific development process in such a field is not very clear, which is also not conducive for researchers to choose and adjust the model. this paper mainly retraces some significant models applied in traffic prediction before and after the advent of neural networks and digs out the reasons for their appearance. through review and mining, we have sorted out the development history of traffic flow prediction models, providing us with some inspiration for subsequent research. © 2022 IEEE.

关键词： Deep learning

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Health status assessment of large complex equipment based on matter-element analysis of equipment historical service environment information 7

Health status assessment of large complex equipment based on...

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2022 7th international Seminar on computer technology, Mechanical and Electrical Engineering, ISCME 2022

作者： Guo, Ming Wu, Fei Li, Biao Zhu, Min College of Nuclear Science and Technology Naval Engineering University Wuhan430033 China

As the level of basic manufacturing increases, large complex equipment often has a high reliability level, leading to a lack of failure data and a more difficult health status assessment. Equipment history service environment information is the natural environment in which the equipment is located, which has an important impact on the health status of the equipment. this paper proposes a method for evaluating the health status of large complex equipment based on a matter-element analysis model using equipment historical service environment information. It can integrate statistically obtainable environmental information, such as temperature and humidity, with non-statistically obtainable environmental information, such as salt spray and random shock, and jointly achieve a quantitative evaluation of the health status of the equipment. the evaluation results show that the method can better integrate the influence of incompatible environmental indicators on the health status of equipment, which is of great significance for making scientific and reasonable decisions on the maintenance of large complex equipment. © Published under licence by IOP Publishing Ltd.

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Non-invasive Haemoglobin Estimation Using Different Colour and Texture Features of Palm 1

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7th international conference on computer Vision and Image processing, CVIP 2022

作者： Kesarwani, Abhishek Das, Sunanda Dalui, Mamata Kisku, Dakshina Ranjan Department of Computer Science and Engineering National Institute of Technology Durgapur India

ISBN: (数字)9783031314179

ISBN: (纸本)9783031314162

Anaemia, caused due to lack of blood haemoglobin levels, is one of the most common diseases which affects billions of people across the world. According to WHO statistics, India is one of the developing countries with highest prevalence of anaemia. Conventional invasive methods are cost-prohibitive and difficult to administer globally which essentially demands non-invasive, accurate, and low-cost approaches for screening of anaemia. the current work targets to combine cutting edge computational approaches with the age-old practice of rough estimation of blood haemoglobin levels by observing pallor in the palm to develop a non-invasive reliable anaemia detection system. the proposed system works with the principle of inducing pallor changes in palm with suitable pressure application and release, measuring the rate of change of colour and performing time-domain analysis thereof to correlate with blood haemoglobin concentration. the entire event of colour changes in palm induced through a customized device, is videophotographed using smartphone camera sensor and is processed and analysed through a set of image processing and analysis techniques. Different handcrafted colour and texture feature extraction techniques are applied on some of the dominant frames considering different colour models on the video samples. the set of features selected throughfeatureselectiontechniques areprovidedas input tomulti-layer perceptron (MLP) networks comprising of different activation functions and optimizers. the proposed system ensures an accurate estimation of blood haemoglobin level with an average RMSE of 0.597 as determined based on palm pallor video samples of 41 participants. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Feature Selection

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Advanced Bank Security and Management System 7

Advanced Bank Security and Management System

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7th IEEE international conference for Convergence in technology, I2CT 2022

作者： Sharma, Keshav Goyal, Yashika Jain, Deepanshu Khanna, Kritika Information Technology Dr. Akhilesh das Gupta Institute of Technology and Management New Delhi India Computer Science Engineering Dr. Akhilesh das Gupta Institute of Technology and Management New Delhi India

ISBN: (纸本)9781665421683

In the prevailing scenario, Net banking plays an essential role in economic development. However, with the increasing significance of digital versions of banking facilities, frauds and scams are exceptionally rising. Moreover, the existing portal of government banks does not provide complete information to their customers regarding various schemes and investment policies. this paper proposes an upgraded design to the current system. It will make online banking reliable and much more efficient. A verification link is sent via Firebase to gain access to the portal. the user can check his eligibility criteria for various active schemes, insurances, and loan capacity. the portal is integrated with third-Party Apps to track the IP address and region of the device trying to log in, which is sent along with a verification link when a transaction gets initiated. After verification, the video recording gets initiated and saved in the portal's cloud storage simultaneously. the person's face inducting the payment gets matched with all faces added by the primary user, using Microsoft Azure Face API. On successful recognition, a correct OTP input completes the transaction process. the principal objective of this paper is to provide countermeasures against possible security breaches at several stages. this design will eliminate the possibility of scams to an admirable extent and ensure that the account holders are well aware of the schemes they can apply. © 2022 IEEE.

关键词： Face recognition

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A Dynamic Algorithm for Submodular Maximization with a Knapsack Constraint 23

A Dynamic Algorithm for Submodular Maximization with a Knaps...

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23rd IEEE international conference on High Performance Computing and Communications, 7th IEEE international conference on Data Science and Systems, 19th IEEE international conference on Smart City and 7th IEEE international conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC-DSS-SmartCity-DependSys 2021

作者： Zhu, Tianshuai Han, Kai Zhang, Enpei Wu, Benwei School of Computer Science and Technology University of Science and Technology of China Hefei China

ISBN: (纸本)9781665494571

Submodular maximization is a fundamental problem in computer science theory, as well as occupies a significant place in machine learning and data mining applications, including influence maximization in social networks, recommendation systems, exemplar-based clustering, viral marketing, and data summarization. In this paper, we study this classic problem under a knapsack constraint in a fully dynamic setting. Given a stream of arbitrary interleaved element insertions and deletions, the dynamic setting requires a solution quickly after each update. By adopting repeated sampling, threshold greedy and filtering technique, our algorithm achieves an approximation ratio of 1/3 for monotone submodular objective function, with polylogarithmic amortized update time. We extensively evaluate the performance of our algorithm against the existing work in two applications including maximum coverage and movie recommendation. the experimental results demonstrate the superiority of our algorithm. © 2021 IEEE.

关键词： Machine learning algorithms Social networking (online) Smart cities Filtering Heuristic algorithms Machine learning Approximation algorithms

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Group member’s importance evaluation algorithm based on identity similarity 7

Group member’s importance evaluation algorithm based on ide...

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2022 7th international conference on information Science, computer technology and Transportation, ISCTT 2022

作者： Sun, Baibing Han, Yi Zhang, Qiao Du, Yanhui College of Information and Cyber Security People's Public Security University of China Beijing China School of Criminology People’s Public Security University of China Beijing China

ISBN: (纸本)9783800760565

Research on the importance ranking of members in a certain group is an important branch in social-network, but the existing importance algorithms ignore the influence of the members' identities differences on the importance assessment. To solve this problem, this paper proposes a K-shell Level based on Identity Similarity (KSL-IS) algorithm to measure the importance of social network members. According to the group members’ link structure, the KSL-IS algorithm defines the identity similarity among members, integrates the location characteristics of members and the influence of neighbourhood members, and comprehensively evaluates the importance of members. this study used four different complex networks as experimental data, compared with existing algorithms, and verified by the Susceptible-Infectious (SI) propagation performance experiment, robustness test, and Kendall correlation coefficient. the investigation showed that the KSL-IS algorithm is more accurate to measure the importance of members in the group. this study verifies that identity and location characteristics should be taken into account when calculating the importance of members. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Complex networks

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An Efficacious Classifier for Recognition of Traffic Symbols 1

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7th international conference on Internet of things and Connected Technologies, ICIoTCT 2022

作者： Virmani, Deepali Parikh, Ketan School of Engineering & Technology Vivekananda Institute of Professional Studies-Technical Campus New Delhi India Department of Computer Science Engineering Bhagwan Parshuram Institute of Technology New Delhi India

ISBN: (数字)9789811997198

ISBN: (纸本)9789811997181

information gathering refers to collecting information from different sources in order to process it to obtain useful information. In particular, image classification refers to the use of several computer algorithms to classify images to extract useful information and as to what they symbolize. It is one of the deep learning methods. Traffic symbols are important to be noticed while driving any vehicle. this paper proposes an image classifier to classify and detect traffic symbols from the dataset of traffic symbols. the proposed algorithm for image classification provides an efficient and accurate way to classify the traffic signal images into classes and the obtained results have great precision. this image classifier can detect the traffic symbols in real time with an accuracy of 88.76%. Various datasets can be chosen to perform experiments with the resulting image classifier. © 2023, the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image classification

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Visual Sensitivity Aware Rate Adaptation for Video Streaming via Deep Reinforcement Learning 23

Visual Sensitivity Aware Rate Adaptation for Video Streaming...

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作者： Dan, Meng Ye, Jin Jiang, Wenchao Shan, Yuanchao Guangxi Key Laboratory of Multi-media Communications and Network Technology Nanning530000 China School of Computer and Electronic Information Guangxi University Nanning530000 China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore

ISBN: (纸本)9781665494571

Adaptive bitrate (ABR) technology is widely adopted in video streaming to improve quality of experience (QoE). However, existing methods ignore the inherent characteristic of Human Visual System (HVS), i.e., HVS has different sensitivity to the quality distortion of different video content. therefore, video contents with high visual sensitivity have higher visual importance and need to be allocated more bitrate resources. In this paper, we propose a novel rate adaptive algorithm by incorporating newly-defined visual sensitivity model. More specifically, a set of relevant features are extracted from video content to establish a deep neural network model that accurately reflects the visual sensitivity. the network state, buffer occupancy and visual sensitivity are comprehensively considered under deep reinforcement learning framework to select appropriate bitrate for maximizing QoE. Experimental results show that the proposed algorithm can generate an ABR strategy consistent with visual sensitivity, and improves the perceptual video quality and user QoE by 14.2% and 16.3%, respectively. © 2021 IEEE.

关键词： Visualization Adaptation models Sensitivity Heuristic algorithms Bit rate Reinforcement learning Streaming media

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the UNICT-TEAM Vision Modules for the Mohamed Bin Zayed international Robotics Challenge 2020 7th

The UNICT-TEAM Vision Modules for the Mohamed Bin Zayed Inte...

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7th international conference on computer Vision and Image processing, CVIP 2022

作者： Battiato, Sebastiano Cantelli, Luciano D’Urso, Fabio Farinella, Giovanni Maria Guarnera, Luca Guastella, Dario Calogero Leonardi, Rosario Noce, Alessia Li Muscato, Giovanni Piazza, Alessio Ragusa, Francesco Santoro, Corrado Sutera, Giuseppe Zappala, Antonio Department of Math and Computer Science University of Catania Catania Italy Department of Electrical Electronic and Computer Engineering University of Catania Catania Italy

Real-world advanced robotics applications cannot be con72;ceived without the employment of onboard visual perception. By per72;ception we refer not only to image acquisition, but more importantly to the informat... 详细信息

ISBN: (纸本)9783031314063

Real-world advanced robotics applications cannot be con¬ceived without the employment of onboard visual perception. By per¬ception we refer not only to image acquisition, but more importantly to the information extraction required to carry out the robotic task. In this paper the computer vision system developed by the team of the Uni¬versity of Catania for the Mohamed Bin Zayed international Robotics Challenge 2020 is presented. the two challenges required to: 1) develop a team of drones for grasping a ball attached to another flying vehi¬cle and to pierce a set of randomly placed balloons, 2) to build a wall by adopting a mobile manipulator and a flying vehicle. Several aspects have been taken into account in order to obtain a real-time and robust system, which are crucial features in demanding situations such as the ones posed by the challenges. the experimental results achieved in the real-world setting are reported. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Object recognition

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Traffic Sparing Algorithm for Multi-Layer Multi-Domain Optical Networks Based on Matching Game 7

Traffic Sparing Algorithm for Multi-Layer Multi-Domain Optic...

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2022 7th international conference on information Science, computer technology and Transportation, ISCTT 2022

作者： Wu, Qiwu Liu, Jiaqi Zheng, Mingzhu Jiang, Lingzhi School of Equipment Management and Support Engineering University of PAP Xi’an710086 China School of Information Engineering Engineering University of PAP Xi’an710086 China

ISBN: (纸本)9783800760565

A matching game based multicast traffic sparse algorithm is proposed for multicast traffic sparse problem in multi-layer multi-domain optical network by fusing matching game and heuristic algorithm. the heuristic algorithm is optimized and the nodes in the optical network are matched effectively to achieve the traffic sparing purpose. the algorithm analysis and experimental results show that the algorithm is significantly effective in reducing the number of transceivers in the optical network, while reducing the network resources and cost investment, and substantially alleviating the possible blocking situation in multicast services. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Fiber optic networks

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